Wealth advisors used to succeed by making insightful lunch conversation, being fun on the golf course and winning referrals. These days, effectively leveraging big data is a better bet for successful marketing.
The growing hoard of wealth invested with robo-advisor platforms is forcing advisers to change how they operate. By the end of 2017, $US160 billion of assets will be invested in digital advice platforms, up from $US65 billion a year ago, according to research by Aite Group and Broadridge. That number will swell to $US400 billion by the end of 2018. Competition from these low-priced services and the trend of replacing mutual funds with lower-priced ETFs, is compressing fees to such an extent that advisers will need to add more clients in order to generate the same fees.
Using data will help advisers get there. Just as Amazon can harness data to predict what you will shop for and data helps Netflix predict which TV series you’ll want to watch, advisers today can leverage a huge reservoir of data to reveal everything from what’s going on in a client’s personal and professional life to how they want to communicate about their money decisions.
Artificial intelligence capabilities can filter and analyse data to help advisers grow the assets being managed for existing clients, and also market to new clients in a more targeted way. AI programs can crunch an incredible amount of information about existing clients to find which clients have more assets held in other accounts and are the ones that advisers should pursue. Broadridge research reveals that as many as one-third of all clients fall into this category.
For marketing to new clients, data can be used to develop marketing campaigns targeting specific sub-segments based on demographics and psychographic information. Firms will be able to target granular subsectors — pediatricians that own their own medical practice in Connecticut, for example. Serving specific groups will make referrals even more effective because a firm can build a reputation for helping meet the needs of a specific micro-segment.
These methods have already been used to great effect by the credit card industry. For example, Capital One uses analytics of consumer spending patterns to introduce credit cards that meet specific customer needs. That approach has helped it become the tenth-largest bank in the United States.
In the future, cutting edge applications will be able to generate recommendations from lists of available investments and products, market events and financial plans of individual customers. Such technology might one day be able to read the facial expressions of a client during video meetings to reveal their unspoken opinions about certain investment recommendations.
Getting the most from technology will be crucial because 41% of Millennials want technology-enabled financial planning tools, according to a recent Roubini ThoughtLab survey. Just like in the credit card business, the firms that succeed and grow in this new environment are the ones that make the best use of data.
Steve Scruton is President at Broadridge Advisor Solutions.